WOBURN, Mass., 7 June 2006. The Department of Defense has awarded five Small Business Innovation Research (SBIR) Phase II awards, totaling $3.74 million, to Aptima Inc., a company involved in human-centered engineering. Aptima was invited to apply for the five Phase II awards by the U.S. Army and Air Force Research Laboratory (AFRL) based on its past Phase I SBIR efforts.
The five contracts include:
Simulation of Cultural Identities for Prediction of Reactions (SCIPR) is a simulation tool to predict the reactions of culturally diverse groups to U.S.-based events or adversarial actions. By modeling responses and behaviors to what-if scenarios, SCIPR helps gauge the effects of alternative courses of action on the identities and belief systems of friends, foes, and ambivalent groups.
Ersatz Brain Project is a computing architecture based on human neurology, to enable future software applications, such as natural language understanding, concept-based internet search, natural human-computer interfaces, cognitively based data-mining, and image analysis. The architecture is based on the future use of massive parallel computing employing approximately 1 million simple CPUs.
TRACE-SE is a resource to help engineers better design and incorporate cognitive capabilities into newly designed systems. By improving the fit between humans and technology, TRACE-SE will help create battle systems that better support the warfighter's ability to understand, react, and make fast-paced combat decisions.
WorkRITE -- This research supports the challenge of how to organize the flow of information and the tools used as the military moves to an increasingly network-centric architecture requiring faster response times across distributed environments. WorkRITE will help to ensure that the right people do the right tasks at the right time in changing, real-time workflow collaboration environments.
PERFORM is a predictive tool that helps determine the relationship between simulator design and training effectiveness. It will aid training designers in determining what knowledge and skills can effectively be trained within simulators of varying levels of fidelity.
